Microscopic Simulation Approach Research Articles

Evaluating the environmental benefits of autonomous vehicles in urban intersections: a microscopic simulation approach

This research delves into the environmental and energy implications of incorporating autonomous vehicles (AVs) into urban traffic systems, mainly focusing on emissions and fuel efficiency. The study employed PTV VISSIM simulation software to model a four-leg signalized intersection in Balgat, Ankara, under varying levels of AV integration and driving behaviors. A total of 21 scenarios were simulated, assessing the impact of cautious, normal, aggressive, and platooning AV behaviors on emissions of CO, NOx, and VOCs, as well as fuel consumption, across different traffic signal cycle durations. The results indicate that shorter signal cycle times consistently significantly reduce emissions and fuel consumption, irrespective of AV driving behavior. The most notable improvements were observed in platooning scenarios, attributed to their optimized traffic flow. In contrast, longer cycle times increased emissions and fuel consumption, especially with human-driven and cautious AVs, due to more frequent idling and stop-and-go traffic patterns. This study highlights the importance of refining AV driving algorithms and optimizing signal control systems to reduce environmental impacts and improve fuel efficiency in urban settings, providing crucial insights for advancing sustainable urban mobility and traffic management strategies.

Advances in terminal management: simulation of vehicle traffic in container terminals

AbstractControlling and managing traffic flows on internal roads in container terminals are crucial in achieving expected productivity levels and reducing negative externalities caused by congestion inside and outside the terminal areas. This paper proposes a simulation approach which terminal operators can use as a decision-support tool to assess the effects of their management strategies and improve terminal performance, resilience, and sustainability. A microscopic traffic simulation approach models key operations of a typical container terminal affecting road traffic flows. In particular, to estimate quantitative indicators, an import truck process is reproduced, considering the overlapping of the external truck and internal trailer flows. To measure environmental impacts, the model is extended with an instantaneous emissions model linked directly to the step-by-step traffic data. The proposed method is tested on a sector of the PSA Genova Pra’, the main Italian container gateway terminal. Performance indicators related to the terminal’s efficiency and sustainability are estimated, to compare alternative scenarios considering possible operational configurations and disturbance events, such as the closure of a part of the yard. By focusing on the interactions between vehicle flows and terminal equipment operations, this approach offers a new perspective on terminal operations, oriented both towards container terminal operators and stakeholders, such as road hauliers.

Platooning of connected automated vehicles on freeways: a microsimulation approach

The platooning of connected automated vehicles (CAVs) is a promising cooperative driving strategy, especially suited for freeway uninterrupted traffic. This paper presents a microscopic simulation approach to the modelling of CAV platooning on freeways, addressing the most relevant factors for the improvement of traffic throughputs. The paper introduces the algorithms to be added to current simulation software so that CAV platoons can be adequately modelled. The goodness of the proposed methodology has been tested through its implementation in the Aimsun Next software and with the application to a mixed traffic scenario consisting of a three-lane ring-road with one on-ramp and one off-ramp, in which platooning is restricted to the leftmost lane. In this context, platooning has shown to increase traffic throughput significantly for CAV penetration rates over 25%. For a 50% penetration rate the infrastructure baseline capacity more than doubles.

Long-Distance Electric Truck Traffic: Analysis, Modeling and Designing a Demand-Oriented Charging Network for Germany

The majority of freight in Germany is carried out by trucks, resulting in emitting approximately 9% of Germany’s carbon dioxide equivalent emissions. In particular, long-distance truck journeys contribute significantly to these emissions. This paper aims to explore the conditions and impacts of introducing E-Trucks in Germany by utilizing a microscopic traffic simulation approach. Therefore, five different electrification levels of the long-distance truck traffic are evaluated. The demand-oriented charging network dimensioning aims for a realistic and implementable design and is based on an average charging power of 720 kW. Additionaly, it considers the necessary infrastructure requirements at service and rest areas next to the motorway. The results of this research provide valuable insights in terms of usage, requirements and demand. For an electrification level of 1%, 177 chargers at 173 charging sites must be implemented, while 1296 chargers and 457 charging sites must be built for an electrification level of 20%. The increase in the electrification level leads to more efficient occupancy of the charging facilities; i.e., an increase from 1% to 5% improves the average occupation time ratio per charger by approximately 130%. Of the total energy consumed, 65% is recharged en-route at public chargers. Between Monday and Thursday, each 1% electrification level increase requires 2.68 GW h more energy for the public recharging network.

Autonomous vehicles impact assessment on congested motorways

Research is still needed to model autonomous vehicles (AVs) to faithfully reflect their behaviours and the reactions of human drivers. This study used a microscopic traffic simulation approach to assess the impact of AVs on both traffic performance and safety performance of a heavily congested motorway according to two traffic management strategies, reserved lane and shared space, materialised in two scenarios corresponding to 25% and 50% AVs fleet penetration. We found that the shared space traffic management strategy significantly improved traffic flow and reduced predicted two-vehicle crashes as the percentage of AVs increased, although a non-negligible increase in the severity of both potential conflicts and crashes may occur. It has been proven that, during the transition period, it is impossible to improve the performance of the road network without worsening safety.

A digital twin in transportation: Real-time synergy of traffic data streams and simulation for virtualizing motorway dynamics

The introduction of digital twins is expected to fundamentally change the technology in transportation systems, as they appear to be a compelling concept for monitoring the entire life cycle of the transport system. The advent of widespread information technology, particularly the availability of real-time traffic data, provides the foundation for supplementing predominated (offline) microscopic simulation approaches with actual data to create a detailed real-time digital representation of the physical traffic. However, the use of actual traffic data in real-time motorway analysis has not yet been explored. The reason is that there are no supporting models and the applicability of real-time data in the context of microscopic simulations has yet to be recognized. Thus, this article focuses on microscopic motorway simulation with real-time data integration during system run-time. As a result, we propose a novel paradigm in motorway traffic modeling and demonstrate it using the continuously synchronized digital twin model of the Geneva motorway (DT-GM). We analyze the application of the microscopic simulator SUMO in modeling and simulating on-the-fly synchronized digital replicas of real traffic by leveraging fine-grained actual traffic data streams from motorway traffic counters as input to DT-GM. Thus, the detailed methodological process of developing DT-GM is presented, highlighting the calibration features of SUMO that enable (dynamic) continuous calibration of running simulation scenarios. By doing so, the actual traffic data are directly fused into the running DT-GM every minute so that DT-GM is continuously calibrated as the physical equivalent changes. Accordingly, DT-GM raises a technology dimension in motorway traffic simulation to the next level by enabling simulation-based control optimization during system run-time that was previously unattainable. It, thus, forms the foundation for further evolution of real-time predictive analytics as support for safety–critical decisions in traffic management. Simulation results provide a solid basis for the future real-time analysis of an extended Swiss motorway network.

Microscopic Simulation Approach to Capacity Analysis of Bus Rapid Transit Corridors

While a transitway can be built as an access-controlled, two-way rapid transit facility outside the Central Business District (CBD), in the CBD, initially, the Bus Rapid Transit (BRT) service has to be based on exclusive bus lanes due to right-of-way, monetary, and other constraints. The strategy of providing Bus Rapid Transit on exclusive bus lanes in urban corridors is receiving policy attention. However, detailed studies on exclusive bus lane capacity for BRT operation in the CBD of a city have been scarce. In this research, using NETSIM as a microsimulator, BRT corridors in Ottawa (Canada) were investigated in terms of their capacity to handle high volumes of transit buses. For these corridors, scenarios incorporating 2021 traffic were analyzed for choke condition and the results were compared with the base case condition representing year 2001 traffic environment. Based on the results of network performance, conclusions were drawn on the capacity of BRT corridors.

Development of Planning-Level Guidelines for Deploying Transit Signal Priority

Transit Signal Priority (TSP) has been proposed and implemented to reduce transit travel time, provide better schedule adherence, and improve transit efficiency. However, concerns have been raised about causing delays to cross street and left-turn movements. The cost-effective implementation of TSP requires methods to support the decisions associated with the implementation. The objective of this research was to examine the existing TSP guidance and propose enhanced planning-level guidelines for TSP deployment that can be applied to identify intersections where implementing TSP is beneficial. The proposed guidelines take consideration of bus delay, bus frequency, geometric and traffic feasibility, as well as the impacts on other movements. The effectiveness of the proposed guidelines was evaluated in comparison with existing guidelines using a microscopic simulation approach. The simulation results showed that the proposed TSP guidelines produce a better-balanced solution for minimizing both main street bus travel times and delays for other affected movements. The proposed guidelines also help to cut the TSP implementation costs by reducing the number of intersections identified for TSP implementation.

Minimizing the Effects of Urban Mobility-on-Demand Pick-Up and Drop-Off Stops: A Microscopic Simulation Approach

Short-term disruptions can have a long-lasting negative effect on traffic flow exceeding the duration of the disruption itself. This is especially the case when traffic demand approaches the network’s capacity. On-demand ride-sourcing services like ride-hailing and ride-pooling do not only have an impact on the overall kilometers driven in a network, but also conduct frequent stopping maneuvers to let passengers board and alight. As further growth of such services is expected, municipalities will need to find ways to organize and, if needed, regulate such activities. This paper proposes, evaluates, and discusses two possible methods that can be part of a holistic strategy to mitigate the impacts of frequent mobility-on-demand curbside stops in an urban environment. The first method adapts the positions of stops at an intersection according to real-time signal timings without adding another variable to the already quite complex traffic signal optimization. The second method discusses a temporary reduction of the number of allowed stopping maneuvers on saturated street sections or in other sensitive areas. Both methods are evaluated using microscopic traffic simulation and result in significant reductions of average vehicle delay as well as standard deviation thereof in all investigated traffic demand scenarios. These results indicate that the proposed methods can help to preserve a stable traffic state in situations close to the capacity limit, which is to the benefit of all stakeholders involved.

Stochasticity of disease spreading derived from the microscopic simulation approach for various physical contact networks

COVID-19 has emphasized that a precise prediction of a disease spreading is one of the most pressing and crucial issues from a social standpoint. Although an ordinary differential equation (ODE) approach has been well established, stochastic spreading features might be hard to capture accurately. Perhaps, the most important factors adding such stochasticity are the effect of the underlying networks indicating physical contacts among individuals. The multi-agent simulation (MAS) approach works effectively to quantify the stochasticity. We systematically investigate the stochastic features of epidemic spreading on homogeneous and heterogeneous networks. The study quantitatively elucidates that a strong microscopic locality observed in one- and two-dimensional regular graphs, such as ring and lattice, leads to wide stochastic deviations in the final epidemic size (FES). The ensemble average of FES observed in this case shows substantial discrepancies with the results of ODE based mean-field approach. Unlike the regular graphs, results on heterogeneous networks, such as Erdős–Rényi random or scale-free, show less stochastic variations in FES. Also, the ensemble average of FES in heterogeneous networks seems closer to that of the mean-field result. Although the use of spatial structure is common in epidemic modeling, such fundamental results have not been well-recognized in literature. The stochastic outcomes brought by our MAS approach may lead to some implications when the authority designs social provisions to mitigate a pandemic of un-experienced infectious disease like COVID-19.

Traffic Flow Performance Analysis for Streets Conversion to Pedestrian Streets: A Microscopic Simulation Approach

Traffic Flow Performance Analysis for Streets Conversion to Pedestrian Streets: A Microscopic Simulation Approach

Modeling indoor-level non-pharmaceutical interventions during the COVID-19 pandemic: A pedestrian dynamics-based microscopic simulation approach

Mathematical modeling of epidemic spreading has been widely adopted to estimate the threats of epidemic diseases (i.e., the COVID-19 pandemic) as well as to evaluate epidemic control interventions. The indoor place is considered to be a significant epidemic spreading risk origin, but existing widely-used epidemic spreading models are usually limited for indoor places since the dynamic physical distance changes between people are ignored, and the empirical features of the essential and non-essential travel are not differentiated. In this paper, we introduce a pedestrian-based epidemic spreading model that is capable of modeling indoor transmission risks of diseases during people's social activities. Taking advantage of the before-and-after mobility data from the University of Maryland COVID-19 Impact Analysis Platform, it's found that people tend to spend more time in grocery stores once their travel frequencies are restricted to a low level. In other words, an increase in dwell time could balance the decrease in travel frequencies and satisfy people's demands. Based on the pedestrian-based model and the empirical evidence, combined non-pharmaceutical interventions from different operational levels are evaluated. Numerical simulations show that restrictions on people's travel frequency and open hours of indoor places may not be universally effective in reducing average infection risks for each pedestrian who visit the place. Entry limitations can be a widely effective alternative, whereas the decision-maker needs to balance the decrease in risky contacts and the increase in queue length outside the place that may impede people from fulfilling their travel needs. The results show that a good coordination among the decision-makers can contribute to the improvement of the performance of combined non-pharmaceutical interventions, and it also benefits the short-term and long-term interventions in the future.

Pengaruh Hambatan Samping terhadap Kapasitas Dasar Jalan Perkotaan Kota Balikpapan dengan Pendekatan Simulasi Mikroskopik

The objective of this research is to show the impact of the side friction to ideal capacity on the urban road based on a microscopic simulation approach. Simulation using software PTV VISSIM. the kind of side frictions that use are parking/stop vehicle (PSV), slow vehicle (SMW), and entry/exit vehicle (EEV). Simulation divided into 2 steps are the first is to gain the basic model and the second is to gain the impact of side friction to ideal capacity. The result shows that the side friction that gives the highest impact to ideal capacity is entry/exit vehicle (EEV), especially on an undivided road. The other result shows that the combination of side friction is not give a cumulative impact on decreasing ideal capacity. That indicates that the combination side friction simulation has a proportional impact on the decreasing of ideal capacity. This research can be an alternative method to analyze the urban traffic characteristics in Indonesia.

Study of work zone traffic safety under adverse driving conditions with a microscopic traffic simulation approach

Work zone traffic safety under adverse weather conditions has been a serious concern for drivers and transportation agencies. Existing studies on work zone traffic safety with statistical approaches are limited by the availability of data from historical crashes. To date, there is no comprehensive simulation framework to assess work zone traffic safety under adverse driving environments by considering both multi-vehicle and single-vehicle crashes. To fill this gap, this paper presents an integrated framework to evaluate traffic safety in work zone under adverse driving conditions by considering specific work zone configuration, weather and road surface conditions. A new risk index is introduced to assess the traffic safety risk of work zones by integrating the risks of multi-vehicle crashes and single-vehicle crashes. Traffic safety of a typical work zone under different weather conditions is studied to demonstrate the proposed framework. The impacts of the differential speed limits (DSL) and truck proportion on the work zone traffic safety are also investigated. Results show that adverse weather may increase the crash risk in work zones. The effect of DSL on the work zone traffic safety is found to be insignificant while the truck ratio influences the work zone safety in the rainy and snowy weather by primarily affecting the multi-vehicle crash risks.

Impact of faster freight trains on railway capacity and operational quality

In view of the transition towards climate-friendly transportation, mobility and freight traffic demand are both expected to grow in Europe´s already heavily occupied railway networks. To accommodate the increasing traffic volume, capacity-optimised traffic planning is a requirement. One key factor in this context is the heterogeneity of train speeds on heavily used mixed-traffic railway lines. In this paper, we study the effects of train speed harmonisation based on the increase of freight train velocities. Two planning scenarios are addressed: In the first case, freight trains have a conventional speed profile but can occasionally make use of their higher allowed speed level when needed. This can be used in operations to recover from delays or blend in with passenger traffic. In the second case, freight trains are scheduled to so called express train paths, reaching a more homogeneous timetable profile. The two planning concepts are analysed and compared in a microscopic simulation approach. It is shown that scenarios based on the first planning concept tend to have positive effects on operational quality and capacity, whereas scenarios using express freight train paths are less promising in this respect.

Simulation Model to Support Security Screening Checkpoint Operations in Airport Terminals

Since 2001 the Transportation Security Administration (TSA) has implemented security screening checkpoints (SSCPs) in the terminals of 440 airports in the U.S.A. The purpose of SSCPs is to prevent prohibited items from being brought onto aircraft. The screening procedure incurs delay to every traveler. This article reports the development of a discrete event simulation model capable of modeling the screening procedures within a SSCP in detail. The model replicates a SSCP at Phoenix Sky Harbor International Airport (PHX) and represents the equipment and activities in the SSCP with 153 nodes, 106 links, two sources, two sinks, and 35 servers. The coded model was calibrated with field data collected primarily at PHX. The potential applications of the model were demonstrated via two experiments: (a) increasing the number of TSA staff; (b) reducing the number of screening lanes. The experiments demonstrated that this microscopic simulation approach captured the queue length and waiting time of every internal process within the SSCP. These performance data helped to identify the hot spots within the SSCP so that improvements to the waiting time could be made by focusing on the problematic components.

A Comparison of Deep Learning Methods for Urban Traffic Forecasting using Floating Car Data

Cities today must address the challenge of sustainable mobility, and traffic state forecasting plays a key role in mitigating traffic congestion in urban areas. For example, predicting path travel time is a crucial issue in navigation and route planning applications. Furthermore, the pervasive penetration of information and communication technologies makes floating car data an important source of real-time data for intelligent transportation system applications. This paper deals with the problem of forecasting urban traffic when floating car data is available. A comparison of four deep learning methods is presented to demonstrate the capabilities of the neural network approaches (recurrent and/or convolutional) in solving the traffic forecasting problem in an urban context. Different tests are proposed in order to not only evaluate the developed deep learning models, but also to analyze how the penetration rates of floating cars affect forecasting accuracy. The presented experiments were designed according to a microscopic traffic simulation approach in order to emulate floating car data fleets, which provide vehicle position and speed, and to validate the obtained results. Finally, some conclusions and further research are presented.

Evaluation of travel delay and accident risk at moving work zones

This study aims to examine the effects of moving work-zone speed, working lane position, and traffic condition on the travel delay, crash risk, and mortality risk at moving work zones by using microscopic traffic simulation approaches. Two surrogate safety measures including TTC (Time to Collision) and Delta-V are employed to represent the vehicle crash risk and mortality risk, respectively. The simulation experiment is conducted based on the observation data from the road network located in the Haidian District of Beijing. Simulation results show that the moving work-zone speed exhibits higher effects on the travel delay, vehicle crash risk, and mortality risk under the smooth traffic state, as compared with those under the congested traffic state. Greater travel delay and higher crash risk are closely associated with the lanes where there are a larger proportion of vehicles whereas the highest mortality risk is for vehicles traveling in the fast lane. The simulation results also show that the vehicles near the moving work zone are associated with high vehicle crash risk, whereas an increased crash risk is also found for the vehicles far from the moving work zone.

Enhancing traffic safety at school zones by operation and engineering countermeasures: A microscopic simulation approach

Safety issues at school zones have been an important topic in the traffic safety field. This study assesses the safety effects of different roadway countermeasure at school zones. Although several studies have evaluated the effectiveness of various traffic control devices (e.g., sign, flashing beacon), there is lack of studies proposing innovative operation and engineering countermeasures, which might have significant improvement of safety at school zones. In this study, the most crash-prone school zone is identified based on crash rates in Orange and Seminole Counties in Florida. Afterward, a microsimulation network is built to evaluate different safety countermeasures. Three different countermeasures i.e., two-step speed reduction, decreasing the number of driveways, and replacing the two-way left-turn lane (TWLTL) with raised median are implemented in the microsimulation. Multiple surrogate safety measures are utilized as indicators for safety evaluation. The results show that both two-step speed reduction and decreasing driveway access significantly reduce crash risks compared with the base condition. Moreover, the combination of these two countermeasures outperforms their individual effectiveness. On the other hand, for TWLTL to the raised median, the crash risk is higher than the base condition. The results of this study could help transportation planners and decision makers to understand the effect of these countermeasures prior to implementing them in the real field.

Evaluating the Environmental Benefits of Median Bus Lanes: Microscopic Simulation Approach

Median bus lanes are an important element of bus rapid transit (BRT) systems, and can improve traffic operations by separating bus traffic from the traffic in general-purpose lanes. Thus, the operation of BRT systems with dedicated bus lanes is expected to reduce energy consumption and produce positive environmental impacts to a substantial degree. This study attempts to quantify the impacts for a corridor in Seoul, South Korea where frequent bus services are provided, using an integrated simulation tool composed of a microscopic traffic model and a vehicle emissions simulator. This approach has rarely been applied for evaluating the environmental benefits of BRT systems. Given a high volume of bus traffic, the simulation results reveal that corridor energy consumption can be reduced by 18.5% and emissions can be reduced by 19.3–31.4%, depending on the pollutant (CO, CO2, PM10, PM2.5, NOx). Vehicles in general-purpose lanes contribute 99.0% of the emissions reductions, with the remaining 1.0% contributed by transit buses. Considering that vehicles in general-purpose lanes represent 94% of corridor traffic, and provide 99.0% of the emission reduction contribution, the simulations suggest that median bus lanes benefit not only the bus operations, but also significantly improve the traffic flow in the general-purpose lanes, contributing to the overall corridor emissions reductions.